Deep Learning with Differential Privacy

1 Jul 201610 code implementations

Machine learning techniques based on neural networks are achieving remarkable results in a wide variety of domains.

Deep Residual Learning for Image Recognition

CVPR 2016 172 code implementations

Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.

IMAGE CLASSIFICATION OBJECT DETECTION SEMANTIC SEGMENTATION

ShakeDrop Regularization for Deep Residual Learning

7 Feb 20186 code implementations

In this paper, to relieve the overfitting effect of ResNet and its improvements (i. e., Wide ResNet, PyramidNet, and ResNeXt), we propose a new regularization method called ShakeDrop regularization.

Xception: Deep Learning with Depthwise Separable Convolutions

CVPR 2017 14 code implementations

We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution followed by a pointwise convolution).

IMAGE CLASSIFICATION

Deep Image Retrieval: Learning global representations for image search

5 Apr 20163 code implementations

We propose a novel approach for instance-level image retrieval.

IMAGE RETRIEVAL

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

19 Nov 2015140 code implementations

In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications.

CONDITIONAL IMAGE GENERATION UNSUPERVISED REPRESENTATION LEARNING

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

18 Oct 20166 code implementations

The approach combines, in a black-box fashion, multiple models trained with disjoint datasets, such as records from different subsets of users.

TRANSFER LEARNING

PyTorch: An Imperative Style, High-Performance Deep Learning Library

NeurIPS 2019 1 code implementation

Deep learning frameworks have often focused on either usability or speed, but not both.

CNTK: Microsoft's Open-Source Deep-Learning Toolkit

ACM SIGKDD 2016 1 code implementation

This tutorial will introduce the Computational Network Toolkit, or CNTK, Microsoft's cutting-edge open-source deep-learning toolkit for Windows and Linux.

DIMENSIONALITY REDUCTION